{"id":1425,"date":"2026-05-24T15:29:31","date_gmt":"2026-05-24T15:29:31","guid":{"rendered":"https:\/\/lean-app.com\/?p=1425"},"modified":"2026-05-24T17:58:07","modified_gmt":"2026-05-24T17:58:07","slug":"lean-vs-noom","status":"publish","type":"post","link":"https:\/\/lean-app.com\/en\/lean-vs-noom\/","title":{"rendered":"Lean vs Noom: psychological coaching vs metabolic precision"},"content":{"rendered":"<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp\" fetchpriority=\"low\">\n<link 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18px;border-radius:14px;color:#fff;font-family:var(--font-display);font-weight:500;font-size:15px;letter-spacing:-.01em;display:flex;justify-content:space-between;align-items:center;box-shadow:0 6px 18px rgba(0,0,0,.06)}\n#lvm-shell .pyramid .level .k{font-family:var(--font-mono);font-size:10px;text-transform:uppercase;letter-spacing:.08em;opacity:.75}\n#lvm-shell .pyramid .l1{background:#0E0E10;width:100%}\n#lvm-shell .pyramid .l2{background:#1D1D1F;width:84%}\n#lvm-shell .pyramid .l3{background:#3a3a3c;width:68%}\n#lvm-shell .pyramid .l4{background:var(--pink);width:52%}\n#lvm-shell .pyramid-cap{text-align:center;font-size:13px;color:var(--muted);margin-top:14px}\n\n\/* Section 7 honnetete : scorecard horizontal bars *\/\n#lvm-shell .scorecard{margin:30px 0 10px;border:1px solid var(--rule);border-radius:20px;padding:28px 26px;background:#fff}\n#lvm-shell .scorecard-head{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding-bottom:18px;margin-bottom:8px;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-head .h-crit{font-family:var(--font-mono);font-size:11px;font-weight:500;text-transform:uppercase;letter-spacing:.08em;color:var(--muted)}\n#lvm-shell .scorecard-head .h-brand{display:flex;align-items:center;gap:8px;font-family:var(--font-display);font-size:14px;font-weight:600;color:var(--ink)}\n#lvm-shell .scorecard-head .h-brand img{width:22px;height:22px;border-radius:5px;object-fit:cover}\n#lvm-shell .scorecard-row{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding:14px 0;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-row:last-child{border-bottom:0}\n#lvm-shell .scorecard-row .crit{font-size:14px;color:var(--ink);font-weight:500;padding-right:14px}\n#lvm-shell .scorecard-row .bar{display:flex;flex-direction:row-reverse;align-items:center;gap:10px}\n#lvm-shell .scorecard-row .bar .b{flex:1;height:8px;border-radius:99px;background:var(--rule-soft);overflow:hidden;position:relative}\n#lvm-shell .scorecard-row .bar .b > i{display:block;height:100%;border-radius:99px;transition:width 1s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .scorecard-row .bar.lean .b > i{background:var(--pink)}\n#lvm-shell .scorecard-row .bar.mfp .b > i{background:var(--mfp)}\n#lvm-shell .scorecard-row .bar .v{font-family:var(--font-mono);font-size:12px;font-weight:600;color:var(--ink);min-width:32px;text-align:left}\n\n\/* Section 8 pour qui : persona checklist *\/\n#lvm-shell .persona{margin:28px 0 10px;display:grid;grid-template-columns:1fr;gap:14px}\n#lvm-shell .persona-it{display:grid;grid-template-columns:54px 1fr;gap:16px;padding:22px 24px;background:#fff;border:1px solid var(--rule);border-radius:18px;align-items:center}\n#lvm-shell .persona-it.match{background:var(--pink-soft);border-color:rgba(255,45,110,.25)}\n#lvm-shell .persona-it .pic{width:54px;height:54px;border-radius:50%;display:flex;align-items:center;justify-content:center;background:var(--rule-soft);position:relative;font-family:var(--font-mono);font-size:13px;font-weight:600;color:var(--ink)}\n#lvm-shell .persona-it.match .pic{background:var(--pink);color:#fff}\n#lvm-shell .persona-it .pic svg{width:24px;height:24px}\n#lvm-shell .persona-it h4{margin:0 0 4px;font-size:17px;letter-spacing:-.01em}\n#lvm-shell .persona-it p{margin:0;font-size:14px;color:var(--muted);line-height:1.55}\n#lvm-shell .persona-it.match h4{color:var(--ink)}\n\n\/* Section 9 migration : timeline steps *\/\n#lvm-shell .steps{display:grid;grid-template-columns:repeat(5,1fr);gap:14px;margin:28px 0;position:relative}\n#lvm-shell .steps::before{content:\"\";position:absolute;top:14px;left:7px;right:calc(20% - 18px);height:1px;background:linear-gradient(90deg,var(--pink) 0%,var(--rule-soft) 100%);z-index:0}\n#lvm-shell .step{position:relative;padding-top:24px;z-index:1}\n#lvm-shell .step::before{content:\"\";position:absolute;top:8px;left:0;width:14px;height:14px;border-radius:50%;background:var(--pink);border:3px solid #fff;box-shadow:0 0 0 1px var(--rule)}\n#lvm-shell .step .sn{font-family:var(--font-mono);font-size:11px;color:var(--pink);font-weight:600;letter-spacing:.08em}\n#lvm-shell .step h4{margin:6px 0 6px;font-size:15px;letter-spacing:-.01em}\n#lvm-shell .step p{font-size:13px;color:var(--muted);line-height:1.5;margin:0}\n\n\/* Section 10 debloque : feature stack numbered XL *\/\n#lvm-shell .feat-stack{margin:30px 0 10px;border-top:1px solid var(--rule)}\n#lvm-shell .feat-it{display:grid;grid-template-columns:auto 1fr auto;gap:24px;padding:26px 0;border-bottom:1px solid var(--rule);align-items:center}\n#lvm-shell .feat-it .fn{font-family:var(--font-display);font-size:48px;font-weight:600;color:var(--pink);line-height:1;letter-spacing:-.04em;width:74px}\n#lvm-shell .feat-it .ft{font-family:var(--font-display);font-size:22px;font-weight:600;color:var(--ink);letter-spacing:-.015em;line-height:1.25;margin-bottom:6px}\n#lvm-shell .feat-it .fd{font-size:15px;color:var(--muted);line-height:1.55;margin:0}\n#lvm-shell .feat-it .fc{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--muted);font-weight:500}\n#lvm-shell .feat-it:last-child{border-bottom:0}\n\n#lvm-shell .faq{margin:22px 0}\n#lvm-shell .faq details{border-bottom:1px solid var(--rule);padding:20px 0}\n#lvm-shell .faq details:first-of-type{border-top:1px solid var(--rule)}\n#lvm-shell .faq summary{cursor:pointer;list-style:none;display:flex;justify-content:space-between;align-items:center;gap:18px;font-family:var(--font-display);font-size:20px;font-weight:500;letter-spacing:-.015em;color:var(--ink)}\n#lvm-shell .faq summary::-webkit-details-marker{display:none}\n#lvm-shell .faq summary::after{content:\"+\";font-size:24px;color:var(--muted);font-weight:300;line-height:1;transition:transform .25s, color .25s}\n#lvm-shell .faq details[open] summary::after{transform:rotate(45deg);color:var(--pink)}\n#lvm-shell .faq details[open] summary{color:var(--pink)}\n#lvm-shell .faq .ans{margin-top:14px;font-size:16px;color:var(--muted);line-height:1.65}\n\n#lvm-shell .get-band{background:var(--paper-2);border-radius:24px;padding:48px 36px;margin:60px 0 40px;text-align:center}\n#lvm-shell .get-band .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;color:var(--pink);font-weight:600;letter-spacing:.1em;margin-bottom:14px}\n#lvm-shell .get-band h3{font-size:36px;margin:0 0 14px;letter-spacing:-.025em}\n#lvm-shell .get-band p{font-size:16px;color:var(--muted);max-width:480px;margin:0 auto 26px}\n#lvm-shell .get-band .stores{display:flex;justify-content:center;gap:14px;flex-wrap:wrap}\n#lvm-shell .get-band .stores a{line-height:0;transition:transform .15s}\n#lvm-shell .get-band .stores a:hover{transform:translateY(-3px)}\n#lvm-shell .get-band .stores img{height:60px;width:auto;border-radius:11px}\n\n#lvm-shell .sources{font-size:14px;color:var(--muted);line-height:1.7}\n#lvm-shell .sources ol{padding-left:22px}\n#lvm-shell .sources li{margin-bottom:8px}\n\n#lvm-shell footer{padding:50px 0 60px;border-top:1px solid var(--rule);margin-top:40px}\n#lvm-shell footer .row{display:flex;justify-content:space-between;align-items:center;gap:18px;flex-wrap:wrap}\n#lvm-shell footer .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--pink);font-weight:600}\n#lvm-shell footer p{font-size:13px;color:var(--muted);margin:8px 0 0}\n#lvm-shell footer .stores{display:flex;gap:8px}\n#lvm-shell footer .stores img{height:34px;width:auto;border-radius:6px}\n\n#lvm-shell .rev{opacity:0;transform:translateY(12px);transition:opacity .8s cubic-bezier(.22,.61,.36,1),transform .8s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .rev.on{opacity:1;transform:translateY(0)}\n@media (prefers-reduced-motion:reduce){#lvm-shell .rev{transition:none;opacity:1;transform:none}}\n\n@media (max-width:760px){\n  #lvm-shell .nav-row{padding:8px 18px;gap:8px}\n  #lvm-shell .nav-link{display:none}\n  #lvm-shell .nav-stores img{height:24px}\n  #lvm-shell .wrap{padding:0 22px}\n  #lvm-shell .hero{padding:34px 0 0}\n  #lvm-shell h1{font-size:46px;letter-spacing:-.035em}\n  #lvm-shell h1 .alt{font-size:.55em;margin-top:10px}\n  #lvm-shell .dek{font-size:20px}\n  #lvm-shell .hero-stores img{height:42px}\n  #lvm-shell .hero-bottom{grid-template-columns:1fr;gap:28px;margin:30px 0 40px;padding-top:24px;align-items:stretch}\n  #lvm-shell .phone-wrap{order:-1}\n  #lvm-shell .phone{width:240px}\n  #lvm-shell .tap-hint.desktop{display:none}\n  #lvm-shell .tap-hint.mobile{display:block;position:relative;left:auto;top:auto;text-align:center;margin:0 auto 10px;width:100%}\n  #lvm-shell .tap-hint.mobile .th-arrow{position:relative;display:block;margin:6px auto 0;width:34px;height:34px;transform:none;color:var(--pink)}\n  #lvm-shell .snippet{padding:24px 22px}\n  #lvm-shell .snippet p{font-size:18px}\n  #lvm-shell section{padding:48px 0}\n  #lvm-shell h2{font-size:34px;letter-spacing:-.03em}\n  #lvm-shell h3{font-size:24px}\n  #lvm-shell .section-label{margin-bottom:22px}\n  #lvm-shell .statement{padding:24px 0;margin:32px 0}\n  #lvm-shell .statement .num{font-size:44px}\n  #lvm-shell .statement .lbl{font-size:19px}\n  #lvm-shell .fig{padding:20px 14px 14px;border-radius:16px}\n  #lvm-shell .cv-wrap{height:310px}\n  #lvm-shell .method{grid-template-columns:1fr;gap:20px}\n  #lvm-shell .method.flip{grid-template-columns:1fr}\n  #lvm-shell .method.flip .m-phone{order:0}\n  #lvm-shell .mini-row{grid-template-columns:repeat(3,1fr);gap:10px}\n  #lvm-shell .mini-phone{padding:3px;border-radius:18px;border-width:1px;max-width:110px}\n  #lvm-shell .mini-phone .notch{width:42px;height:11px;border-radius:0 0 8px 8px}\n  #lvm-shell .mini-phone .scr{border-radius:15px}\n  #lvm-shell .mini-cap{font-size:10px}\n  #lvm-shell .mini-cap strong{font-size:13px}\n  #lvm-shell .duo-row{grid-template-columns:repeat(2,1fr);gap:12px}\n  #lvm-shell .duo-row .mini-phone{max-width:130px}\n  #lvm-shell .steps{grid-template-columns:1fr;gap:18px}\n  #lvm-shell .steps::before{display:none}\n  #lvm-shell .step{padding-top:0;padding-left:24px}\n  #lvm-shell .step::before{top:6px;left:0}\n  #lvm-shell .table-row{grid-template-columns:1.4fr .9fr .9fr}\n  #lvm-shell .table-row > .crit{padding:13px 12px;font-size:13px}\n  #lvm-shell .table-row > .cell{padding:13px 10px;font-size:12px;gap:8px}\n  #lvm-shell .table-row.head > div{padding:14px 12px;font-size:10px;gap:7px}\n  #lvm-shell .table-row.head .brand-cell img{width:20px;height:20px}\n  #lvm-shell .get-band{padding:36px 22px;border-radius:18px;margin:40px 0 30px}\n  #lvm-shell .get-band h3{font-size:28px}\n  #lvm-shell .get-band .stores img{height:50px}\n  #lvm-shell .cta-band{padding:22px;gap:14px}\n  #lvm-shell .cta-band .l{font-size:16px;min-width:0}\n  #lvm-shell .cta-band .stores img{height:38px}\n  #lvm-shell .faq summary{font-size:18px;gap:14px}\n  #lvm-shell .pyramid{max-width:100%}\n  #lvm-shell .pyramid .level{padding:11px 14px;font-size:14px}\n  #lvm-shell .scorecard{padding:20px 16px;border-radius:16px}\n  #lvm-shell .scorecard-head{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px}\n  #lvm-shell .scorecard-head .h-brand{font-size:12px;gap:5px}\n  #lvm-shell .scorecard-head .h-brand img{width:18px;height:18px}\n  #lvm-shell .scorecard-row{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px;padding:12px 0}\n  #lvm-shell .scorecard-row .crit{font-size:13px;padding-right:8px}\n  #lvm-shell .scorecard-row .bar{gap:6px}\n  #lvm-shell .scorecard-row .bar .v{font-size:11px;min-width:26px}\n  #lvm-shell .persona-it{grid-template-columns:44px 1fr;gap:12px;padding:16px 16px;border-radius:14px}\n  #lvm-shell .persona-it .pic{width:44px;height:44px;font-size:12px}\n  #lvm-shell .persona-it h4{font-size:15px}\n  #lvm-shell .persona-it p{font-size:13px}\n  #lvm-shell .feat-it{grid-template-columns:auto 1fr;gap:14px;padding:20px 0}\n  #lvm-shell .feat-it .fn{font-size:36px;width:54px}\n  #lvm-shell .feat-it .ft{font-size:18px}\n  #lvm-shell .feat-it .fd{font-size:13px}\n  #lvm-shell .feat-it .fc{display:none}\n}\n@media (max-width:480px){\n  #lvm-shell .phone-tabs{gap:5px}\n  #lvm-shell .phone-tabs button{padding:5px 8px;font-size:10px}\n  #lvm-shell .nav-stores{gap:4px}\n  #lvm-shell .nav-stores img{height:22px}\n  #lvm-shell .hero-stores img{height:40px}\n  #lvm-shell .crumb{font-size:12px}\n  #lvm-shell .table-row{grid-template-columns:1.3fr .85fr .85fr}\n  #lvm-shell .table-row > .crit{padding:11px 9px;font-size:12px}\n  #lvm-shell .table-row > .cell{padding:11px 8px;font-size:11px;gap:6px}\n  #lvm-shell .table-row.head > div{padding:11px 9px;font-size:9px;gap:5px}\n}<\/style>\n\n<style id=\"lvm-collision-reset\">\n\/* Hard reset for global theme styles that collide with our content *\/\nbody.postid-1425 #lvm-shell .hero{display:block!important;align-items:initial!important;justify-content:initial!important;text-align:left!important;flex-direction:initial!important;padding:54px 0 0!important}\nbody.postid-1425 #lvm-shell .wrap,\nbody.postid-1425 #lvm-shell main.wrap{display:block!important;max-width:760px!important;margin-left:auto!important;margin-right:auto!important;padding-left:28px!important;padding-right:28px!important}\n@media (max-width:820px){\n  body.postid-1425 #lvm-shell .wrap,\n  body.postid-1425 #lvm-shell main.wrap{padding-left:18px!important;padding-right:18px!important}\n}\nhtml, body{overflow-x:hidden!important}\nbody.postid-1425 #lvm-shell{overflow-x:hidden;max-width:100vw}\nbody.postid-1425 #lvm-shell *{max-width:100%}\nbody.postid-1425 #lvm-shell .nav-row{max-width:100vw;box-sizing:border-box}\nbody.postid-1425 #lvm-shell.force-show .rev{opacity:1!important;transform:none!important}\n\n\/* === A.1 PHONE BACKGROUND CLASSES === *\/\nbody.postid-1425 #lvm-shell .phone-bg{position:absolute;inset:0;width:100%;height:100%;background-size:cover;background-position:center top;background-repeat:no-repeat;transition:opacity .28s ease;background-color:#FAF0E6}\nbody.postid-1425 #lvm-shell .phone-bg.tab-depense{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.tab-bilan{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.tab-kcal{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.tab-strategie{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.sub-BMR{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.sub-NEAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.sub-EAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.sub-TEF{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp)}\n\n\/* === v11.3 CTA BANDS MOBILE (badges plus gros + centrage) === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .cta-band{flex-direction:column!important;align-items:center!important;text-align:center!important;padding:26px 22px!important;gap:20px!important}\n  body.postid-1425 #lvm-shell .cta-band .l{min-width:0!important;width:100%!important;font-size:16px!important;line-height:1.5!important;text-align:center!important}\n  body.postid-1425 #lvm-shell .cta-band .stores{width:100%!important;justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1425 #lvm-shell .cta-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1425 #lvm-shell .cta-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1425 #lvm-shell .cta-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n  body.postid-1425 #lvm-shell .get-band{padding:38px 22px!important}\n  body.postid-1425 #lvm-shell .get-band .stores{justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1425 #lvm-shell .get-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1425 #lvm-shell .get-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1425 #lvm-shell .get-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n  body.postid-1425 #lvm-shell .get-band h3{font-size:26px!important;line-height:1.2!important}\n  body.postid-1425 #lvm-shell .get-band p{font-size:15px!important}\n}\n\n\/* === v11.2 BRAND BANNER above table responsive === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .brand-banner img{width:54px!important;height:54px!important}\n  body.postid-1425 #lvm-shell .brand-banner > div{padding:16px 12px!important;gap:8px!important}\n  body.postid-1425 #lvm-shell .brand-banner > div > div{font-size:15px!important}\n}\n\n\/* === v11.4 SCORECARD partie 7: redesign mobile === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .scorecard{padding:18px 16px!important;border-radius:16px!important}\n  body.postid-1425 #lvm-shell .scorecard-head{display:none!important}\n  body.postid-1425 #lvm-shell .scorecard-row{\n    display:block!important;\n    padding:14px 0!important;\n    border-bottom:1px solid #E8E2D6!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .crit{\n    display:block!important;\n    font-size:13px!important;\n    font-weight:600!important;\n    color:#0E0E10!important;\n    margin-bottom:10px!important;\n    padding-right:0!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .bar{\n    display:grid!important;\n    grid-template-columns:54px 1fr 32px!important;\n    column-gap:8px!important;\n    align-items:center!important;\n    padding:5px 0!important;\n    flex-direction:initial!important;\n    position:relative!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .bar::before{\n    content:attr(data-brand)!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:11px!important;\n    font-weight:600!important;\n    text-transform:uppercase!important;\n    letter-spacing:.05em!important;\n    color:#0E0E10!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .bar.lean::before{color:#FF2D6E!important}\n  body.postid-1425 #lvm-shell .scorecard-row .bar.mfp::before{color:#5B7FFF!important}\n  body.postid-1425 #lvm-shell .scorecard-row .bar .b{\n    height:10px!important;\n    width:100%!important;\n    border-radius:99px!important;\n    position:relative!important;\n    background:#EFEAE0!important;\n    overflow:hidden!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .bar .b > i{\n    display:block!important;\n    height:100%!important;\n    border-radius:99px!important;\n  }\n  body.postid-1425 #lvm-shell .scorecard-row .bar .v{\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:12px!important;\n    font-weight:700!important;\n    color:#0E0E10!important;\n    min-width:0!important;\n    text-align:right!important;\n  }\n}\n\n\/* === A.2 CHARTS MOBILE === *\/\n@media (max-width:760px){\n  \/* v13: charts FULL WIDTH (less card padding) + plus hauts pour vraie respiration *\/\n  body.postid-1425 #lvm-shell .cv-wrap{height:380px!important;min-height:360px!important;max-height:420px!important;width:100%!important}\n  body.postid-1425 #lvm-shell .cv-wrap canvas{width:100%!important;height:100%!important;display:block!important}\n  body.postid-1425 #lvm-shell .fig{padding:16px 4px 14px!important;margin:24px -4px 14px!important;overflow:visible!important}\n  body.postid-1425 #lvm-shell .fig-head{padding:0 12px!important;flex-wrap:wrap!important;gap:6px!important;margin-bottom:10px!important}\n  body.postid-1425 #lvm-shell .fig-body{padding:0 2px!important}\n  body.postid-1425 #lvm-shell .fig-cap{padding:0 12px!important;font-size:13px!important;margin-top:10px!important}\n}\n@media (max-width:480px){\n  body.postid-1425 #lvm-shell .cv-wrap{height:360px!important;min-height:340px!important;max-height:380px!important}\n  body.postid-1425 #lvm-shell .fig{padding:14px 2px 12px!important;margin:20px -6px 12px!important;border-radius:14px!important}\n  body.postid-1425 #lvm-shell .fig-body{padding:0!important}\n}\n\n\/* === v11.2 TABLEAU MOBILE STACKED CARDS avec mini-tags Lean\/MFP === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .table{border-radius:14px!important}\n  body.postid-1425 #lvm-shell .table-row.head{display:none!important}\n  body.postid-1425 #lvm-shell .table-row{\n    display:grid!important;\n    grid-template-columns:1fr 1fr!important;\n    grid-template-areas:\"crit crit\" \"lean mfp\"!important;\n    gap:0!important;\n    min-height:0!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .crit{\n    grid-area:crit!important;background:#0E0E10!important;color:#fff!important;\n    padding:11px 14px!important;font-size:13px!important;font-weight:600!important;\n    letter-spacing:-0.1px!important;border-right:0!important;line-height:1.35!important;\n    font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif!important;text-transform:none!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .cell.lean{\n    grid-area:lean!important;border-right:1px solid #E8E2D6!important;\n    position:relative!important;background:#FFF1F5!important;padding-top:30px!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .cell:not(.lean):not(.crit){\n    grid-area:mfp!important;background:#F5F5F7!important;padding-top:30px!important;\n    position:relative!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .cell.lean::before{\n    content:\"LEAN\"!important;position:absolute!important;top:8px!important;left:12px!important;\n    right:auto!important;bottom:auto!important;width:auto!important;height:auto!important;\n    background:transparent!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:10px!important;font-weight:700!important;letter-spacing:.07em!important;\n    color:#FF2D6E!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .cell:not(.lean):not(.crit)::before{\n    content:\"NOOM\"!important;position:absolute!important;top:8px!important;left:12px!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:10px!important;font-weight:700!important;letter-spacing:.07em!important;\n    color:#FF6E5E!important;\n  }\n  body.postid-1425 #lvm-shell .table-row > .cell{\n    padding:12px 12px!important;font-size:13px!important;line-height:1.4!important;\n    align-items:flex-start!important;gap:7px!important;\n  }\n  body.postid-1425 #lvm-shell .icn{flex-shrink:0!important;margin-top:1px!important}\n}\n\n\/* === A.5 MINI-LOGOS partie 7 (triplet NEAT\/EAT\/TEF) === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .mini-row{gap:6px!important;margin:24px 0!important;grid-template-columns:repeat(3,1fr)!important}\n  body.postid-1425 #lvm-shell .mini-phone{max-width:100px!important;padding:2px!important;border-radius:14px!important;border-width:1px!important}\n  body.postid-1425 #lvm-shell .mini-phone.tiny{max-width:96px!important;padding:2px!important;border-radius:13px!important}\n  body.postid-1425 #lvm-shell .mini-phone .notch{width:30px!important;height:8px!important;border-radius:0 0 5px 5px!important}\n  body.postid-1425 #lvm-shell .mini-phone .scr{border-radius:11px!important}\n  body.postid-1425 #lvm-shell .mini-cap{font-size:10px!important;margin-top:8px!important}\n  body.postid-1425 #lvm-shell .mini-cap strong{font-size:12px!important;margin-top:2px!important}\n}\n\n\/* === MOCKUP TAP HINT MOBILE === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .tap-hint.mobile{position:relative!important;width:100%!important;left:auto!important;top:auto!important;text-align:center!important;margin:0 auto 14px!important;display:block!important}\n  body.postid-1425 #lvm-shell .tap-hint.desktop{display:none!important}\n  body.postid-1425 #lvm-shell .tap-hint.hidden{display:none!important;height:0!important;margin:0!important;padding:0!important}\n}\n\n\/* === A.6 BODYSCAN ILLUST partie BMR (override mobile mini-phone) === *\/\nbody.postid-1425 #lvm-shell .bodyscan-illust{margin:40px auto 8px!important;display:flex!important;flex-direction:column!important;align-items:center!important;gap:14px!important;max-width:220px!important}\nbody.postid-1425 #lvm-shell .bodyscan-illust .mini-phone{max-width:200px!important;padding:3px!important;border-radius:22px!important;border-width:1px!important}\nbody.postid-1425 #lvm-shell .bodyscan-illust .mini-phone .notch{width:40px!important;height:11px!important;border-radius:0 0 7px 7px!important}\nbody.postid-1425 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:18px!important}\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .bodyscan-illust{max-width:180px!important}\n  body.postid-1425 #lvm-shell .bodyscan-illust .mini-phone{max-width:160px!important;padding:3px!important;border-radius:20px!important}\n  body.postid-1425 #lvm-shell .bodyscan-illust .mini-phone .notch{width:34px!important;height:9px!important;border-radius:0 0 6px 6px!important}\n  body.postid-1425 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:16px!important}\n}\n<\/style>\n\n\n<div id=\"lvm-shell\"><div class=\"progress\" aria-hidden=\"true\"><i id=\"progBar\"><\/i><\/div>\n\n<header class=\"nav\">\n  <div class=\"nav-row\">\n    <a class=\"nav-brand\" href=\"https:\/\/lean-app.com\/en\/\" aria-label=\"Lean home\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/>\n      <span>Lean<\/span>\n    <\/a>\n    <span class=\"nav-spacer\"><\/span>\n    <a class=\"nav-link\" href=\"https:\/\/lean-app.com\/en\/tdee-calculator\/\">TDEE Calculator<\/a>\n    <div class=\"nav-stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\" aria-label=\"Download on the App Store\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n      <\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\" aria-label=\"Get it on Google Play\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n      <\/a>\n    <\/div>\n  <\/div>\n<\/header>\n\n<main class=\"wrap\">\n\n<section class=\"hero\" aria-labelledby=\"title\">\n  <div class=\"crumb\"><a href=\"https:\/\/lean-app.com\/en\/\">Home<\/a> &nbsp;\/&nbsp; Lean vs Noom<\/div>\n  <div class=\"eyebrow\">Comparison &middot; Nutrition &amp; TDEE<\/div>\n  <h1 id=\"title\">Lean versus Noom.\n    <span class=\"alt\">Psychological coaching versus metabolic precision.<\/span>\n  <\/h1>\n  <p class=\"dek\">Noom sells behavioral coaching to change your habits. Lean sees your real expenditure. Two promises that don&rsquo;t play on the same field.<\/p>\n  <div class=\"byline\">\n    <img class=\"by-logo\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/>\n    <span><strong>The Lean team<\/strong> &middot; 12&nbsp;min read &middot; Updated May 24, 2026<\/span>\n  <\/div>\n  <div class=\"hero-stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T\u00e9l\u00e9charger sur l'App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Disponible sur Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <span class=\"or\">Free download<\/span>\n  <\/div>\n\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      Noom is known for its long, personalized sign-up quiz, its daily food-psychology lessons, its green\/yellow\/red food classification, and access to a human coach. A real strength for adherence and habit work. But its TDEE formula remains Mifflin-St Jeor 1990, plus a static activity factor you tick once during the sign-up quiz. No real bodyfat measured inside the app, no metabolic adaptation. Over 3 months of a serious cut, the gap widens.\n    <\/div>\n    <div class=\"phone-wrap rev\">\n      <div class=\"phone-stage\">\n        <div class=\"tap-hint mobile\" id=\"tapHintMobile\" aria-hidden=\"true\">\n          <span class=\"th-pill\"><small>Interactive demo<\/small>Tap the screen to explore the app<\/span>\n          <svg class=\"th-arrow\" viewbox=\"0 0 24 24\" fill=\"none\" aria-hidden=\"true\">\n            <path d=\"M12 4 L12 20 M5 13 L12 20 L19 13\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\n          <\/svg>\n        <\/div>\n        <div class=\"tap-hint desktop\" id=\"tapHintDesktop\" aria-hidden=\"true\">\n          <span class=\"th-pill\"><small>Interactive demo<\/small>Tap the screen<br>to explore the app<\/span>\n          <svg class=\"th-arrow\" viewbox=\"0 0 104 34\" fill=\"none\" aria-hidden=\"true\">\n            <path d=\"M4 9 C 34 1, 64 20, 94 27\" stroke=\"currentColor\" stroke-width=\"2.6\" fill=\"none\" stroke-linecap=\"round\"\/>\n            <path d=\"M86 20 L 94 27 L 84 30\" stroke=\"currentColor\" stroke-width=\"2.6\" fill=\"none\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\n          <\/svg>\n        <\/div>\n        <div class=\"phone\" id=\"phone\" role=\"img\" aria-label=\"Preview of the Lean app with TDEE drill-down\">\n          <div class=\"notch\"><\/div>\n          <div class=\"phone-screen\">\n            <button class=\"phone-back\" id=\"phoneBack\" aria-label=\"Back\">&#8249;<\/button>\n            <div id=\"phoneImg\" class=\"phone-bg tab-depense\" role=\"img\" aria-label=\"Lean preview, Expenditure tab\"><\/div>\n            <div class=\"phone-zones\" id=\"phoneZones\">\n              <div class=\"z\" data-sub=\"BMR\"  style=\"top:11%;height:21%\" role=\"button\" tabindex=\"0\" aria-label=\"BMR detail\"><\/div>\n              <div class=\"z\" data-sub=\"NEAT\" style=\"top:33%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"NEAT detail\"><\/div>\n              <div class=\"z\" data-sub=\"EAT\"  style=\"top:50%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"EAT detail\"><\/div>\n              <div class=\"z\" data-sub=\"TEF\"  style=\"top:67%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"TEF detail\"><\/div>\n            <\/div>\n            <div class=\"phone-navbar\" id=\"phoneNav\" aria-hidden=\"false\">\n              <button data-tab=\"bilan\"     type=\"button\" aria-label=\"Summary tab\"><\/button>\n              <button data-tab=\"kcal\"      type=\"button\" aria-label=\"Calories tab\"><\/button>\n              <button data-tab=\"depense\"   type=\"button\" aria-label=\"Expenditure tab\"><\/button>\n              <button data-tab=\"strategie\" type=\"button\" aria-label=\"Strategy tab\"><\/button>\n            <\/div>\n          <\/div>\n        <\/div>\n        <div class=\"phone-tabs\" role=\"tablist\" aria-label=\"Navigate the Lean app\">\n          <button data-tab=\"bilan\"     type=\"button\">Overview<\/button>\n          <button data-tab=\"kcal\"      type=\"button\">Calories<\/button>\n          <button data-tab=\"depense\"   type=\"button\" class=\"on\">Expenditure<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Strategy<\/button>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">Quick answer<\/div>\n    <p>Noom calculates your TDEE with Mifflin-St Jeor 1990 (no bodyfat measured inside the app) and a static activity factor chosen during the sign-up quiz. Noom&rsquo;s real strength is elsewhere: a personalized quiz that creates strong initial engagement, daily food-psychology lessons, a green\/yellow\/red food classification, and access to a human coach who works on adherence. Lean takes a different stance: recalculate every component of TDEE (<span data-term=\"BMR\">BMR<span class=\"tt\">Basal Metabolic Rate. Energy expended at rest. In Lean, calculated on actual lean mass via BodyScan AI.<\/span><\/span> on real bodyfat via a patented proprietary model, <span data-term=\"NEAT\">NEAT<span class=\"tt\">Non-Exercise Activity Thermogenesis. Expenditure from steps and daily activities outside of sport.<\/span><\/span> from steps, <span data-term=\"EAT\">EAT<span class=\"tt\">Exercise Activity Thermogenesis. Expenditure tied to sport sessions, calculated through MET.<\/span><\/span> via MET, <span data-term=\"TEF\">TEF<span class=\"tt\">Thermic Effect of Food. Energy spent on digestion. Depends on the macros you eat.<\/span><\/span> per macros) and modulate the BMR through metabolic adaptation continuously, with no coefficient to pick.<\/p>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"constat\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">00 &middot; The reality<\/span><\/div>\n  <h2 id=\"constat\">Noom sells coaching, not your metabolic adaptation<\/h2>\n  <p>If you&rsquo;re reading this, you&rsquo;ve probably already installed Noom. You took the long sign-up quiz, those 20 minutes of very personal questions about your history with weight, your blocks, your emotions, your habits. You felt understood. You entered your weight, your height, your age, your sex, and picked your activity level from a static list. The app showed you a calorie target, say 1,500&nbsp;kcal to lose weight.<\/p>\n  <p>You followed the daily 5 to 10 minute lessons on food psychology. You classified your meals as green, yellow, red. You chatted with your human coach on tough days. For the first 6 weeks, it works. You lose. You&rsquo;re happy. Then around week 8, the scale freezes. You tighten the screws. You drop to 1,350&nbsp;kcal. Still nothing moves.<\/p>\n\n  <div class=\"statement\">\n    <div class=\"num\">&minus;10 to &minus;15&nbsp;%<\/div>\n    <div class=\"lbl\">of measured TDEE decline after 4 to 6 weeks of a &minus;500&nbsp;kcal\/day deficit. Noom doesn&rsquo;t detect it. Your calorie target stays frozen on the activity factor you ticked during the sign-up quiz, 100&nbsp;days ago.<\/div>\n  <\/div>\n\n  <p>Imagine Noom shows you a TDEE of 2,000&nbsp;kcal. You eat 1,500 (theoretical deficit of 500&nbsp;kcal). But in reality, your <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/total-daily-energy-expenditure-tdee\/\">TDEE has dropped to 1,700&nbsp;kcal<\/a> due to metabolic adaptation. You&rsquo;re only at a 200&nbsp;kcal real deficit, not 500. Loss slows drastically. No daily Noom lesson can fix that, because the problem isn&rsquo;t in your head, it&rsquo;s in the equation.<\/p>\n  <p>The Noom promise is clear and delivered on its behavioral side: you feel supported, you work on your emotional triggers, you learn to classify the quality of your choices. It&rsquo;s valuable for adherence. What Noom doesn&rsquo;t do is <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/comment-compter-ses-calories\/\">recompute your expenditure<\/a> as weeks of deficit go by. And that's exactly where the \"calorie tracker\" promise stops, even though it's the lever that actually drives weight loss.<\/p>\n<\/section>\n\n<section aria-labelledby=\"p1\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">01 &middot; Problem 1<\/span><\/div>\n  <h2 id=\"p1\">The 1990 BMR formula, with no bodyfat measured in the app<\/h2>\n  <p>To calculate your basal metabolic rate (the BMR, the energy you burn at rest), Noom uses the Mifflin-St Jeor equation. It&rsquo;s the canonical formula of most mainstream calorie trackers, and to be fair: it&rsquo;s better than the Harris-Benedict 1919 that some other apps still use.<\/p>\n  <p>Mifflin-St Jeor dates from 1990. The sample is larger (498 subjects), the indirect calorimetry methodology is more precise, the formula is calibrated on a more modern population. Noom applies the official formula: 10 \u00d7 weight (kg) + 6.25 \u00d7 height (cm) &minus; 5 \u00d7 age &minus; 161 (women) or +5 (men).<\/p>\n  <p>Unlike some competitors that offer an advanced Katch-McArdle equation as an option (based on lean mass), <strong>Noom offers no lean-mass fallback<\/strong>. No manual bodyfat input, no Katch-McArdle computation, no DEXA input. You are locked into Mifflin by default, period. The consequence is mechanical: two users at the same weight but with 10 and 30 percent bodyfat get <strong>the same Noom BMR<\/strong>, whereas their real expenditure can differ by 400 to 500 kcal per day.<\/p>\n  <p>Mifflin (1990) marginally improves on Harris-Benedict (1919) for average accuracy, but inherits the same conceptual flaw: <strong>the formula only accounts for weight. Not bodyfat. Not lean mass.<\/strong><\/p>\n  <p>Yet since the 1980s, we've known that <strong>fat mass burns very little energy<\/strong> compared to the rest of the body. The liver, brain, heart, kidneys, and especially muscles are the real energy sinks. Fat mass is inert. Someone at 30% bodyfat does not burn anywhere near as much as someone at 10% bodyfat, even at identical weight.<\/p>\n  <p>Frankenfield 2013 (PubMed 23631843) compared Mifflin-St Jeor to reference indirect calorimetry across obese and non-obese cohorts. Result: 87&nbsp;% accuracy in non-obese subjects, and only <strong>75&nbsp;% in obese subjects<\/strong>. A more recent study (PMC11820646) shows that for BMIs above 35, Mifflin is off by <strong>250 to 315&nbsp;kcal per day<\/strong>. That&rsquo;s the equivalent of a whole snack inside a deficit calculation. And Noom&rsquo;s main audience, women aged 35 to 55 on the &laquo;&nbsp;long-term weight loss&nbsp;&raquo; topic, is particularly concerned by these gaps.<\/p>\n\n  <p style=\"margin-bottom:8px\"><strong>Worked example.<\/strong> Woman at 1.65m, 85&nbsp;kg, 38&nbsp;% bodyfat&nbsp;:<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figure 1<\/span><span class=\"r\">kcal<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\"><canvas id=\"chartBMR\" aria-label=\"BMR comparison: Mifflin-St Jeor 1670 kcal vs Lean patented proprietary model 1340 kcal, 330 kcal gap\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Estimated BMR<\/strong> for a woman at 1.65m, 85&nbsp;kg, 38&nbsp;% bodyfat. The patented proprietary Lean model accounts for lean mass. Mifflin-St Jeor (Noom by default, with no lean-mass option), doesn&rsquo;t. A 330&nbsp;kcal gap, the equivalent of a full light meal.<\/p>\n  <\/div>\n\n  <p>330&nbsp;kcal is not nothing. If Noom tells you &laquo;&nbsp;your BMR is 1,670&nbsp;&raquo; and in reality it&rsquo;s 1,340, everything that follows is wrong: your deficit target, your projected weekly loss, your green\/yellow\/red classification calibrated on a wrong calorie budget.<\/p>\n\n  <div class=\"bodyscan-illust\" style=\"margin:40px auto 8px;display:flex;flex-direction:column;align-items:center;gap:14px;max-width:200px\">\n    <div class=\"mini-phone\" style=\"max-width:200px\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-bodyscan-result.webp\" alt=\"BodyScan IA Lean : bodyfat mesur\u00e9 par photo en 5 secondes\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n    <div class=\"mini-cap\">Real bodyfat<strong>Photo, 5 seconds<\/strong><\/div>\n  <\/div>\n\n  <div class=\"statement\">\n    <div class=\"num\">400 kcal<\/div>\n    <div class=\"lbl\">gap between two women at 75&nbsp;kg, one at 22&nbsp;% bodyfat (BMR 1,650), the other at 38&nbsp;% (BMR 1,250). Noom gives them the same number, with no lean-mass option.<\/div>\n  <\/div>\n\n  <p>Partial conclusion: if an app calculates your BMR only from your weight, height, age, and sex, the result cannot be individualized. It&rsquo;s mathematically impossible. No human coach corrects this equation, because the coach doesn&rsquo;t have access to your bodyfat either.<\/p>\n<\/section>\n\n<section aria-labelledby=\"p2\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">02 &middot; Problem 2<\/span><\/div>\n  <h2 id=\"p2\">The activity factor, picked once and for all<\/h2>\n  <p>This is where it gets serious. And it&rsquo;s probably the point your Noom coach didn&rsquo;t explain to you.<\/p>\n  <p>Once Noom has calculated your BMR (without bodyfat measured inside the app), it has to estimate your total TDEE. The <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/total-daily-energy-expenditure-tdee\/\">TDEE is BMR plus everything else<\/a> : expenditure from steps, daily activities, sport, and digestion. Everything that isn't basal metabolism.<\/p>\n  <p>How does Noom do that? The sign-up quiz asks you, only once, to pick your activity level from a static list of a few boxes. In sports science these factors are called <strong>PAL levels<\/strong> (Physical Activity Level), it&rsquo;s just a multiplier applied to your BMR:<\/p>\n  <ul>\n    <li>Sedentary (PAL 1.25): desk job, little walking<\/li>\n    <li>Lightly active (PAL 1.4): occasional walking, little sport<\/li>\n    <li>Active (PAL 1.6): regular walking, sport 3 to 5 times per week<\/li>\n    <li>Very active (PAL 1.8): intense sport almost daily or physical work<\/li>\n  <\/ul>\n  <p>And depending on your choice, the app multiplies your BMR by the associated coefficient. That&rsquo;s it. That&rsquo;s all there is behind your daily calorie target. A box YOU ticked once during the sign-up quiz. Often six months ago. No movement since. No daily Noom lesson will revisit that choice.<\/p>\n  <p>And here&rsquo;s the silent trap: this approximation is <strong>wildly imperfect<\/strong>. The difference between a day glued to the couch in front of Netflix and a day at Disneyland with your kids walking 15&nbsp;km, <strong>over 1,000 kcal<\/strong>. None of the boxes captures this.<\/p>\n  <p>Noom syncs well with Apple Health and Google Fit, and captures your steps. An exercise calorie add-on can be added to the daily calorie target when the app detects a session. But those steps don&rsquo;t feed a recomputation of the full TDEE: your calorie target remains based on the activity factor picked at the sign-up quiz, plus an exercise add-on that blurs NEAT and EAT without separating them cleanly.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figure 2 &middot; 7 real days<\/span><span class=\"r\">kcal\/day<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\"><canvas id=\"chartNEAT\" aria-label=\"Daily variability of caloric expenditure over 7 days, vs 2000 kcal fixed per Noom\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Real expenditure<\/strong> measured over 7&nbsp;days for a Lean user. The grey line is what Noom was showing (2,000&nbsp;kcal flat, PAL Active \u00d7 BMR). The pink annotations show why each day moves.<\/p>\n  <\/div>\n\n  <p>You can&rsquo;t reduce your activity level to a static box. You may be active during the weeks when you chase after your kids and sedentary during the ones when you work remotely. You may be active in summer and sedentary in winter. You may be active Tuesday through Friday and sedentary on weekends.<\/p>\n  <p>Which box will you tick this week? The truth is, none of the boxes will be correct. So Noom will give you a TDEE that is systematically disconnected from reality.<\/p>\n  <p>The key point of this article: even with a more modern BMR formula, the static PAL would be enough to break everything. You cannot estimate a <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/neat-non-exercise-activity-thermogenesis\/\">NEAT<\/a>, EAT and <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/thermic-effect-of-food-tef\/\">TEF<\/a> with a single multiplier on top of BMR. Conceptually absurd.<\/p>\n  <p>You get the idea: <strong>a BMR formula without bodyfat measured inside the app, plus a static PAL approximation of the other expenditure components, gives very little chance of reaching your goals over 3 to 6 months, even with the best psychological coaching in the world.<\/strong><\/p>\n\n  <div class=\"cta-band rev\">\n    <div class=\"l\">See your real TDEE, broken down into BMR + NEAT + EAT + TEF. Free download.<\/div>\n    <div class=\"stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"p3\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">03 &middot; Problem 3<\/span><\/div>\n  <h2 id=\"p3\">Metabolic adaptation, never modeled<\/h2>\n  <p>This is the final boss. The most subtle concept. And probably the most important.<\/p>\n  <p>When you&rsquo;re in a calorie deficit, your body realizes it&rsquo;s receiving less energy than before. To protect itself, it switches to power-saving mode. Exactly like your iPhone&rsquo;s low-power mode: everything keeps working, just using less energy. Your BMR drops. Your NEAT drops. Your EAT drops.<\/p>\n  <p>This is called metabolic adaptation. The scientific literature is clear and reproducible: M&uuml;ller 2015 (PubMed 26399868, Minnesota revisit), Doucet 2001 on adaptation in prolonged deficit, Nunes 2020 (PMC7484122) on 6 weeks of deficit, Chin 2016 on the role of behavioral therapy in weight loss. Here are the numbers:<\/p>\n  <ul>\n    <li>Deficit of &minus;250&nbsp;kcal per day, over 2 to 8 weeks: adaptation of <strong>5 to 10%<\/strong> (TDEE drops to 90-95&nbsp;% of the initial level)<\/li>\n    <li>Deficit of &minus;500&nbsp;kcal per day: <strong>10 to 15%<\/strong> adaptation (TDEE drops to 85-90&nbsp;%)<\/li>\n    <li>Deficit of &minus;750&nbsp;kcal per day: <strong>15 to 25%<\/strong> adaptation (TDEE drops to 75-85&nbsp;%)<\/li>\n  <\/ul>\n  <p>Lean convention: 100&nbsp;% = optimal, 90&nbsp;% = 10&nbsp;% adaptation. And since NEAT, EAT and TEF all depend directly on the BMR, almost the entire TDEE is impacted.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figure 3 &middot; 8 weeks in deficit<\/span><span class=\"r\">kcal\/day<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\"><canvas id=\"chartAdapt\" aria-label=\"TDEE dropping from 2000 to 1720 kcal over 8 weeks, vs 2000 fixed per Noom\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>real TDEE<\/strong> over 8 weeks of deficit at &minus;500&nbsp;kcal\/day. The pink curve drops. The Noom line stays flat. By week 6, you&rsquo;re already at maintenance. Without having changed anything.<\/p>\n  <\/div>\n\n  <p>Concretely: if you had planned a 25&nbsp;% deficit on a TDEE of 2,000 (eating 1,500 per day), and your body adapts by 14&nbsp;%, your real TDEE has shifted to 1,720. You&rsquo;re only at 220&nbsp;kcal real deficit. You no longer lose.<\/p>\n  <p>The trap is that it&rsquo;s insidious. Early on, you lose. You&rsquo;re happy. You keep going. But week after week, adaptation compounds. And at some point, without having changed anything in your tracking, <strong>you stop losing<\/strong>.<\/p>\n  <p>95&nbsp;% of people go through this without understanding it. They blame their willpower. They blame their &laquo;&nbsp;broken metabolism&nbsp;&raquo;. The Noom coach will tell you it&rsquo;s normal, that it will come back, that your habits need to change. You head into harder diets, which worsens adaptation. Spiral.<\/p>\n  <p>Noom never calculates metabolic adaptation. It gives you a fixed, static calorie target as long as you don&rsquo;t manually update your weight and activity level. You can follow daily lessons, rigorously classify your meals green\/yellow\/red week after week, and chat with your coach three times a week, but when you stall after 6 weeks of cut, the app has no idea why. No human coach can fix a TDEE equation he doesn&rsquo;t see.<\/p>\n<\/section>\n\n<section aria-labelledby=\"solution\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">04 &middot; Lean's solution<\/span><\/div>\n  <h2 id=\"solution\">How Lean fixes each of the 3 problems<\/h2>\n  <p>Lean was not built as an improved clone of Noom. Noom has a real edge on mainstream psychological coaching, its sign-up quiz, its daily lessons, and its habit work. Lean was built for the complementary angle: seriously tracking the full TDEE theory (BMR + NEAT + EAT + TEF), with metabolic adaptation as the 5th brick that modulates the BMR continuously. Concretely, here is how Lean handles each component.<\/p>\n\n  <div class=\"method\">\n    <div class=\"m-phone\">\n      <div class=\"duo-row\">\n        <div>\n          <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-bodyscan-result.webp\" alt=\"R\u00e9sultat BodyScan IA : pourcentage de masse grasse mesur\u00e9 par photo\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\">Step 1<strong>BodyScan AI<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp\" alt=\"\u00c9cran BMR Lean : m\u00e9tabolisme de base calcul\u00e9 sur la masse maigre\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\">Step 2<strong>BMR recalculated<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n    <div>\n      <div class=\"m-tag\">BMR on real bodyfat<\/div>\n      <h3>Proprietary patented model, built on lean mass<\/h3>\n      <p>Lean uses a <strong>proprietary patented model<\/strong> which depends directly on lean mass, not raw bodyweight. To do that, the app needs your bodyfat. And here we hit the historically painful problem: how do you measure your bodyfat without paying for a clinic DEXA scan every week?<\/p>\n      <p>Lean&rsquo;s answer: the <strong>BodyScan AI<\/strong>. You take a photo, the app runs it through a model trained on a massive bank of DEXA scans, and you get your estimated bodyfat in seconds. You can redo it every week. The BMR recomputes automatically.<\/p>\n      <p>Goodbye skinfold calipers (imprecise), goodbye bioimpedance scales (unreliable), goodbye DEXA scan (perfect but not accessible weekly). One photo, 5 seconds.<\/p>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">No activity coefficient<\/div>\n      <h3>NEAT, EAT, TEF calculated separately<\/h3>\n      <p><strong>NEAT.<\/strong> Lean pulls your real step count via HealthKit (iOS) or Google Fit (Android). No declaration. No &ldquo;I think I walk enough.&rdquo; Your steps, measured by your smartphone&rsquo;s very precise accelerometers. The <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/neat-non-exercise-activity-thermogenesis\/\">NEAT is computed by crossing those steps with your BMR<\/a>, every day, with no coefficient to pick.<\/p>\n      <p><strong>EAT.<\/strong> For each training session, you pick the sport from a list (strength training, running, tennis, swimming, etc.), and Lean uses the sport&rsquo;s MET (Metabolic Equivalent Task) to compute the real expenditure. You enter the actual time <strong>effective<\/strong> of sport (not the total time with rest periods: the mistake 100&nbsp;% of smartwatches make). A strength session at 1,050&nbsp;kcal according to your Apple Watch? Reality is closer to 200&nbsp;kcal. Lean refuses that drift.<\/p>\n      <p><strong>TEF.<\/strong> Digestion burns energy, and it isn't a flat 10% lump. <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/thermic-effect-of-food-tef\/\">Protein costs 20 to 30%<\/a> of their calories in digestion. Carbs 5 to 10&nbsp;%. Fats 1 to 3&nbsp;%. Lean calculates your real TEF from your macros. On 2,000&nbsp;kcal\/day, that can represent a 70 to 100&nbsp;kcal gap depending on your diet composition.<\/p>\n    <\/div>\n    <div class=\"m-phone\">\n      <div class=\"mini-row\" style=\"margin:0;gap:10px\">\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp\" alt=\"\u00c9cran NEAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">NEAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp\" alt=\"\u00c9cran EAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">EAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp\" alt=\"\u00c9cran TEF Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">TEF<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"method\">\n    <div class=\"m-phone\">\n      <div class=\"mini-phone\" style=\"max-width:170px\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" alt=\"\u00c9cran d\u00e9pense totale Lean avec adaptation m\u00e9tabolique\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Method<strong>Auto adaptation<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"m-tag\">Automatic metabolic adaptation<\/div>\n      <h3>A world first on a consumer app<\/h3>\n      <p>Lean is, to our knowledge, the first app to compute metabolic adaptation automatically. As your weeks in deficit add up, the app adjusts your TDEE downward based on the scientifically established figures (M&uuml;ller 2015, Doucet 2001, Nunes 2020). Convention 100 &rarr; 0&nbsp;%: 100&nbsp;% = optimal, 90&nbsp;% = 10&nbsp;% adaptation. You don&rsquo;t have to do anything. You see your calorie goal readjust gently, with no surprises.<\/p>\n      <p>When you reach 10 to 15&nbsp;% adaptation, the app can advise a return to maintenance to reset your BMR before going back into deficit. Cycle, plateau, cycle. Like in real protocols. No Noom human coach can give you that precision, because no coach measures your adaptation continuously.<\/p>\n      <p>No activity coefficient to pick. No static PAL box. Just every component computed precisely, week after week.<\/p>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"tab\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">05 &middot; Side-by-side<\/span><\/div>\n  <h2 id=\"tab\">Lean versus Noom, criterion by criterion<\/h2>\n  <p>An honest read of each app's strengths and weaknesses. No criterion touches price.<\/p>\n\n  <div class=\"table\" role=\"table\" aria-label=\"Lean vs Noom comparison\">\n    <div class=\"table-row head\" role=\"row\">\n      <div role=\"columnheader\">Criterion<\/div>\n      <div class=\"brand-cell lean\" role=\"columnheader\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>Lean<\/span><\/div>\n      <div class=\"brand-cell\" role=\"columnheader\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/logo-noom-real.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>Noom<\/span><\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">BMR formula<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Proprietary patented model (lean mass)<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Mifflin-St Jeor 1990, no lean-mass option<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Uses bodyfat<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Yes, measured in the app<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No, no bodyfat input possible<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Bodyfat measured inside the app<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> BodyScan AI via photo<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">NEAT (steps, non-exercise activity)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Computed from real steps every day<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> HealthKit sync, exercise calorie add-on, but outside any TDEE recomputation<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">EAT (exercise expenditure)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Per sport via MET, effective time<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Simple sport selection, standard exercise database<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">TEF (digestion)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Calculated from macros, integrated into the TDEE<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No, macros displayed without TEF computation<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Metabolic adaptation<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Automatic, week by week<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Activity multiplier to pick<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> No, computed on real data<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Yes, static level chosen through the sign-up quiz<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">AI photo scan of a meal<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Yes, unlimited<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No, manual entry or barcode<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Barcode scan<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Yes<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Yes<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Food database<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> USDA + OpenFoodFacts, curated<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Proprietary database + green\/yellow\/red classification<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Calorie deficit recommendation<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Adapted to real TDEE<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Fixed target, manual recompute required<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Human coaching and behavioral therapy<\/div>\n      <div class=\"cell lean\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Out of scope, focus on TDEE computation<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Human coaches, groups, daily lessons<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Green\/yellow\/red food classification<\/div>\n      <div class=\"cell lean\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Out of scope<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Mainstream educational reference<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">EU coverage and localization<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> FR, EN, ES, PT, IT, DE, PL, HU<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> EN, ES, DE and others, founded in NYC 2008<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Reputation and audience size<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> 4.7\/5, 10,000+ users, young FR app<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> 4.5\/5, 50M+ downloads, audience women 35-55<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Business model<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Premium, 7-day free trial on the annual subscription<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Paid subscription, short trial period<\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"tracking\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">06 &middot; Tracking<\/span><\/div>\n  <h2 id=\"tracking\">3 ways to track a meal<\/h2>\n  <p>Tracking calories is fine. <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/comment-compter-ses-calories\/\">Doing it for 12 months is another story<\/a>. Principle #1, <strong>before science, before macros, before everything<\/strong>, is adherence. If the tracking method bores you, you quit after 3 weeks. Noom knows this, it&rsquo;s their entire commercial pitch. Lean offers 3 ways to track a meal, without a human coach but with a mechanic of precision and speed:<\/p>\n\n  <div class=\"mini-row\">\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-database.webp\" alt=\"Recherche dans la base de donn\u00e9es USDA + OpenFoodFacts\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Method 1<strong>Database<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-codebarre.webp\" alt=\"Scan de code-barres dans Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Method 2<strong>Barcode<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-scania.webp\" alt=\"Scan photo IA d'un plat\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Method 3<strong>AI photo scan<\/strong><\/div>\n    <\/div>\n  <\/div>\n\n  <ol>\n    <li><strong>Database search.<\/strong> Curated base, USDA + OpenFoodFacts. No community noise, no \"Roast chicken\" entered 47 times by 47 different users with 47 different values.<\/li>\n    <li><strong>Barcode scan.<\/strong> Standard. You scan your pasta box, you get the macros.<\/li>\n    <li><strong>AI photo scan of a meal.<\/strong> You take a photo of your plate, the AI detects the foods, you get calories and macros per food. Noom doesn&rsquo;t offer this feature.<\/li>\n  <\/ol>\n  <p>The AI photo scan is the adherence game changer. When you eat out, at a restaurant, at friends&rsquo; places, it&rsquo;s very convenient. One photo, you close the app, you enjoy your evening. Yes, it&rsquo;s less precise than weighing to the gram on a kitchen scale. But over 12 months, that&rsquo;s the difference between holding on and giving up. And holding on is what counts. Noom bets on the human coach for adherence; Lean bets on minimal tracking friction.<\/p>\n  <p>Beyond meal-by-meal tracking, Lean shows a <strong>live TDEE that updates throughout the day<\/strong>. The more you walk, the more your expenditure rises, the more your daily calorie goal adjusts. You see your calorie balance live. It&rsquo;s more motivating than a number frozen at 8&nbsp;a.m.<\/p>\n  <p>And above all that sits the <strong>Progression Pyramid<\/strong>. It&rsquo;s an app screen that ranks what matters:<\/p>\n\n  <div class=\"pyramid\" aria-label=\"Lean Progression Pyramid\">\n    <div class=\"level l1\"><span>Adherence<\/span><span class=\"k\">Foundation<\/span><\/div>\n    <div class=\"level l2\"><span>Calorie target<\/span><span class=\"k\">Tier 2<\/span><\/div>\n    <div class=\"level l3\"><span>Steps \/ NEAT<\/span><span class=\"k\">Tier 3<\/span><\/div>\n    <div class=\"level l4\"><span>Macronutrients<\/span><span class=\"k\">Peak<\/span><\/div>\n  <\/div>\n  <div class=\"pyramid-cap\">Don&rsquo;t skip steps. If you&rsquo;re not consistent on tracking, optimizing macros to the percent is pointless.<\/div>\n<\/section>\n\n<section aria-labelledby=\"noom-better\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">07 &middot; Honesty<\/span><\/div>\n  <h2 id=\"noom-better\">What Noom does better<\/h2>\n  <p>Lean is not perfect, and Noom has several real strengths worth acknowledging. Honest read, criterion by criterion, on the axes where Noom stays ahead. None of these axes is secondary: they are real pillars of the Noom promise, and they explain its massive adoption among the target audience of women aged 35 to 55 on the long-term weight loss topic.<\/p>\n\n  <div class=\"scorecard rev\" aria-label=\"Noom vs Lean scorecard across 4 axes: psychology and adherence\">\n    <div class=\"scorecard-head\">\n      <div class=\"h-crit\">Axis<\/div>\n      <div class=\"h-brand\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/logo-noom-real.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> Noom<\/div>\n      <div class=\"h-brand\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> Lean<\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Human coaching and behavioral therapy<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:94%\"><\/i><\/div><div class=\"v\">9,4<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:20%\"><\/i><\/div><div class=\"v\">2,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Daily food-psychology lessons<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:92%\"><\/i><\/div><div class=\"v\">9,2<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:25%\"><\/i><\/div><div class=\"v\">2,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Intuitive green\/yellow\/red classification<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:88%\"><\/i><\/div><div class=\"v\">8,8<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:30%\"><\/i><\/div><div class=\"v\">3,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Long-term adherence work<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:90%\"><\/i><\/div><div class=\"v\">9,0<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:70%\"><\/i><\/div><div class=\"v\">7,0<\/div><\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Honest read.<\/strong> On human coaching, Noom is the mainstream reference: your coach chats with you, the support groups (Noom community) run continuously, and it&rsquo;s a real emotional accompaniment for those who need it. On the daily food-psychology lessons (5 to 10 minutes each day, inspired by CBT, cognitive behavioral therapy), Noom has invested massively and it&rsquo;s unique on the market: no other calorie tracker offers this structured educational content. On the green\/yellow\/red classification, it&rsquo;s an intuitive mechanism that saves the user time and works well for profiles who don&rsquo;t want to dive into macros. On long-term adherence, Chin 2016 and many meta-analyses on behavioral therapy applied to weight loss show significant gains at 6 and 12 months. Noom builds scientifically on that axis.<\/p>\n  <p>If your main angle is psychological work on food habits, if you need a human coach to hold on, or if the green\/yellow\/red classification helps you make choices without calculating, Noom is more relevant than Lean. If your angle is the precision of <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/tdee-calculator\/\">TDEE calculation<\/a>, bodyfat measured every week through BodyScan AI, and automatic metabolic adaptation, that&rsquo;s exactly what was demonstrated in the 3 previous sections. Many users run Lean for measurement and Noom in parallel for psychological coaching, which is entirely defensible.<\/p>\n<\/section>\n\n<section aria-labelledby=\"forwho\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">08 &middot; Who it's for<\/span><\/div>\n  <h2 id=\"forwho\">Who Lean is built for<\/h2>\n  <p>4 profiles. If you recognize yourself in at least one, Lean is probably for you.<\/p>\n\n  <div class=\"persona\">\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>You followed Noom seriously and didn&rsquo;t lose<\/h4>\n        <p>You took the quiz, followed daily lessons, classified your meals green\/yellow\/red, chatted with your coach, kept it up for several weeks, and you&rsquo;re stalling. The culprit isn&rsquo;t your willpower, it&rsquo;s the TDEE frozen by Mifflin 1990 without bodyfat that your calorie targets rely on. Lean fixes it at the root through BMR on real bodyfat.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>You plateau after several weeks of cutting<\/h4>\n        <p>Plateau dragging on after 4 to 8 weeks. That&rsquo;s metabolic adaptation. Lean calculates it automatically and readjusts your target every week. No Noom human coach can do this calculation for you.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>You want to understand your metabolism<\/h4>\n        <p>Lean displays each component (BMR, NEAT, EAT, TEF) then explains adaptation separately, instead of hiding everything behind a single number. You see where each kcal of expenditure comes from, rather than a target handed down from on high by the Noom app.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>You want tracking that lasts 12 months<\/h4>\n        <p>AI photo scan + curated database + barcode cover every use case, from raw ingredient to restaurant pizza. That&rsquo;s the difference between holding on and giving up, without depending on a human coach.<\/p>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Noom stays more relevant for<\/strong>&nbsp;: working psychologically on food habits, enjoying a human coach and support groups, following daily lessons of cognitive behavioral therapy applied to weight loss, or relying on the green\/yellow\/red classification to make choices without calculating. Precision of TDEE calculation and metabolic adaptation just aren&rsquo;t part of its main promise.<\/p>\n<\/section>\n\n<section aria-labelledby=\"migrate\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">09 &middot; Migration<\/span><\/div>\n  <h2 id=\"migrate\">Switching from Noom to Lean (or using both) in 3 minutes<\/h2>\n\n  <div class=\"steps\">\n    <div class=\"step\"><div class=\"sn\">01<\/div><h4>Download Lean<\/h4><p>App Store or Play Store. Sign-up in 30 seconds, no 20-minute quiz.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">02<\/div><h4>BodyScan AI<\/h4><p>One photo, 5 seconds. You get your bodyfat.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">03<\/div><h4>Weight &amp; height<\/h4><p>You enter your weight and height. That&rsquo;s it.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">04<\/div><h4>Lean computes<\/h4><p>BMR on real bodyfat, NEAT via HealthKit \/ Google Fit (real steps), EAT via MET, TEF via macros, plus metabolic adaptation that modulates the BMR. Automatic.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">05<\/div><h4>Log a meal<\/h4><p>Photo, barcode or database. You get the flow.<\/p><\/div>\n  <\/div>\n\n  <p style=\"margin-top:24px\"><strong>Important note.<\/strong> Lean doesn&rsquo;t import your Noom history automatically, nor your exchanges with your human coach. If you appreciate Noom&rsquo;s psychological coaching and daily lessons, many users keep using Noom for behavioral work and support groups, while using Lean daily for the TDEE calculation and precise tracking. The HealthKit \/ Google Health Connect sync, on the other hand, takes over immediately for your steps and activity history.<\/p>\n\n  <div class=\"cta-band rev\">\n    <div class=\"l\">Download Lean and start the BodyScan AI right now. Free sign-up.<\/div>\n    <div class=\"stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"deblock-h\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">10 &middot; What Lean unlocks<\/span><\/div>\n  <h2 id=\"deblock-h\">What Lean does, that Noom doesn&rsquo;t (on TDEE)<\/h2>\n  <p>Six features that don&rsquo;t exist in any other mainstream tracker. They all follow from the same principle&nbsp;: calculate every component of TDEE precisely, don&rsquo;t approximate it or wrap it in coaching.<\/p>\n\n  <div class=\"feat-stack\">\n    <div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">Unlimited BodyScan AI<\/div><p class=\"fd\">Your real bodyfat, measured from a simple photo, redone every week. It&rsquo;s the data point that changes the entire BMR calculation. No other mainstream app offers this, and Noom even less.<\/p><\/div><div class=\"fc\">Bodyfat<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">Unlimited AI photo scan of a meal<\/div><p class=\"fd\">Track your restaurant meal in 2 seconds. No scale, no manual entry. The adherence game changer over 12 months, no coach.<\/p><\/div><div class=\"fc\">Adherence<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">Automatic metabolic adaptation<\/div><p class=\"fd\">Your TDEE readjusts week after week according to scientifically established numbers. You avoid the plateaus nobody, not even a Noom human coach, can technically explain.<\/p><\/div><div class=\"fc\">Adaptation<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">Live TDEE breakdown<\/div><p class=\"fd\">BMR + NEAT + EAT + TEF each displayed, updated throughout the day. No more frozen number at 8 AM. You see your calorie balance live.<\/p><\/div><div class=\"fc\">Live<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">Full history and trends<\/div><p class=\"fd\">Track your weight, bodyfat, lean-mass trends over months. Understand your cycles. Spot the phases where you progress and the ones where you stall.<\/p><\/div><div class=\"fc\">History<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">06<\/div><div><div class=\"ft\">3 unified tracking methods<\/div><p class=\"fd\">Photo, barcode, curated database. No other app offers all three with such precision. You choose the method based on context.<\/p><\/div><div class=\"fc\">Tracking<\/div><\/div>\n  <\/div>\n\n  <p style=\"margin-top:26px\">You install the app for free, you test without commitment, then you decide whether the tool fits your goal.<\/p>\n<\/section>\n\n<section aria-labelledby=\"faq-h\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">11 &middot; FAQ<\/span><\/div>\n  <h2 id=\"faq-h\">Frequently asked questions<\/h2>\n  <div class=\"faq\">\n    <details><summary>Noom is known for its psychological coaching, why compare it to Lean on TDEE&nbsp;?<\/summary><div class=\"ans\">Noom is renowned for its behavioral approach (daily CBT-inspired lessons, human coaches, green\/yellow\/red food classification). That&rsquo;s a real strength for adherence and psychological work on eating. But the underlying calorie engine remains Mifflin-St Jeor 1990 without bodyfat, plus a static activity factor chosen through the sign-up quiz. On TDEE, the engine is basic. Lean recalculates your BMR every day on your real bodyfat measured by BodyScan AI, and modulates through metabolic adaptation. The two apps don&rsquo;t play on the same field.<\/div><\/details>\n    <details><summary>Why doesn&rsquo;t Noom calculate the BMR on real bodyfat&nbsp;?<\/summary><div class=\"ans\">Noom applies Mifflin-St Jeor 1990 by default without a lean-mass option. No bodyfat measurement is built into the app, and no Katch-McArdle-type equation is offered even in advanced settings. The consequence is mechanical: two users of the same weight but with 22 and 38 percent bodyfat get the same Noom BMR, while their real expenditure can differ by 400 kcal per day. Lean integrates BodyScan AI to measure your bodyfat from a simple photo, to redo every week.<\/div><\/details>\n    <details><summary>Is Noom&rsquo;s green\/yellow\/red classification a real metabolic measure&nbsp;?<\/summary><div class=\"ans\">No. The green\/yellow\/red system classifies foods by calorie density (vegetables in green, starches in yellow, fats and sugars in red). It&rsquo;s an educational behavioral tool, not a measurement of energy expenditure. It&rsquo;s effective for raising awareness about choices, but it doesn&rsquo;t influence the TDEE calculation. On your real metabolism, Noom stays on Mifflin 1990 plus a few static activity boxes. The color classification doesn&rsquo;t modify the calculated calorie target.<\/div><\/details>\n    <details><summary>Noom imports steps via HealthKit, is that enough for NEAT&nbsp;?<\/summary><div class=\"ans\">Noom imports steps and activity through Apple Health and Google Fit, but uses them to estimate an exercise expenditure added to the daily calorie target. The static activity factor picked at the sign-up quiz remains the base of the TDEE calculation. Lean, on the contrary, calculates NEAT directly from real steps measured every day, with no coefficient to pick.<\/div><\/details>\n    <details><summary>Does Noom&rsquo;s human coaching replace a precise TDEE calculation&nbsp;?<\/summary><div class=\"ans\">Noom&rsquo;s human coaching is a real added value for adherence and psychological work on habits. Chin 2016 and many meta-analyses show that behavioral therapy improves weight loss at 6 and 12 months. But coaching doesn&rsquo;t act on the underlying TDEE equation. If your calorie target is calculated on Mifflin 1990 without bodyfat and a static PAL, your coach won&rsquo;t fix the equation, he&rsquo;ll encourage you to hold a potentially wrong deficit. Coaching is an adherence multiplier, not a substitute for objective measurement.<\/div><\/details>\n    <details><summary>Can you use Lean and Noom in parallel&nbsp;?<\/summary><div class=\"ans\">Yes, it&rsquo;s defensible. If you appreciate Noom&rsquo;s human coaching, daily lessons, and behavioral pedagogy, you can keep Noom for the psychological and habits side. Lean takes care of the precise metabolic engine (BMR on real bodyfat, NEAT, EAT, TEF, adaptation). The databases are different (USDA + OpenFoodFacts on the Lean side, proprietary database on the Noom side) so the double-entry effort is real: it&rsquo;s a trade-off to arbitrate based on your priorities.<\/div><\/details>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"conclu\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">12 &middot; Conclusion<\/span><\/div>\n  <h2 id=\"conclu\">Coaching versus measurement<\/h2>\n  <p>It&rsquo;s not Noom versus Lean in marketing. It&rsquo;s psychological coaching versus metabolic precision, two different promises.<\/p>\n  <p>Noom remains one of the best mainstream apps for behavioral work on eating, and nobody in the mainstream does better on daily food-psychology lessons and human-coach accompaniment. But for your TDEE, Noom uses Mifflin-St Jeor 1990 without bodyfat measured inside the app, plus a frozen activity factor you tick once during the sign-up quiz, and ignores metabolic adaptation. The combination of all three makes any precise calorie tracking impossible beyond a few weeks of cut. It&rsquo;s mathematics. No human coach corrects an equation he doesn&rsquo;t see.<\/p>\n  <p>Lean was built to do the exact opposite: BMR based on <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/total-daily-energy-expenditure-tdee\/\">real bodyfat<\/a> (measured by BodyScan AI) via a proprietary patented model, <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/neat-non-exercise-activity-thermogenesis\/\">NEAT from real steps<\/a>, EAT per sport via MET, <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/thermic-effect-of-food-tef\/\">TEF from macros<\/a>, plus metabolic adaptation that modulates the BMR week after week. Each component calculated precisely, no magic coefficient, no psychological wrapping.<\/p>\n  <p>Noom remains very solid on behavioral coaching and human accompaniment. The best results often come from combining the two: measuring right (Lean) AND acting with discipline (sometimes helped by a Noom coach). If you tried Noom seriously and didn&rsquo;t get the results you hoped for on your cut, the problem isn&rsquo;t you, nor Noom on its psychological promise. The problem is the TDEE frozen under the hood. Change the engine, keep the coach alongside if you need it.<\/p>\n<\/section>\n\n<div class=\"get-band rev\">\n  <div class=\"kicker\">Download<\/div>\n  <h3>Lean is available as a free download<\/h3>\n  <p>iOS and Android. The BodyScan AI works from a single photo. No skinfold calliper, no bioimpedance scale, no DEXA.<\/p>\n  <div class=\"stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\" aria-label=\"Download Lean on the App Store\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\" aria-label=\"Download Lean on Google Play\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n  <\/div>\n<\/div>\n\n<section aria-labelledby=\"links\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">Further reading<\/span><\/div>\n  <h3 id=\"links\" style=\"margin-top:0\">Internal links<\/h3>\n  <ul>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/tdee-calculator\/\">Free online TDEE calculator<\/a> &middot; web version, no sign-up, same logic as the app (BMR + NEAT + EAT + TEF).<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/total-daily-energy-expenditure-tdee\/\">Understand TDEE in depth (BMR, NEAT, EAT, TEF, adaptation)<\/a> &middot; deep-science article.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/comment-compter-ses-calories\/\">How to count your calories properly<\/a> &middot; practical guide for beginners.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/neat-non-exercise-activity-thermogenesis\/\">NEAT: expenditure from steps and non-exercise activity<\/a>.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/thermic-effect-of-food-tef\/\">TEF: digestion burns calories<\/a>.<\/li>\n  <\/ul>\n<\/section>\n\n<section aria-labelledby=\"src\" class=\"sources\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">Sources<\/span><\/div>\n  <h3 id=\"src\" style=\"margin-top:0;color:var(--ink)\">Bibliography<\/h3>\n  <ol>\n    <li>Harris J.A., Benedict F.G. (1919). A Biometric Study of Basal Metabolism in Man. Carnegie Institution of Washington.<\/li>\n    <li>Mifflin M.D. et al. (1990). A new predictive equation for resting energy expenditure in healthy individuals. American Journal of Clinical Nutrition.<\/li>\n    <li>Katch V.L., McArdle W.D. (1973). Prediction of body density from simple anthropometric measurements in college-age men and women. Human Biology.<\/li>\n    <li>Chin S.O. et al. (2016). Successful weight reduction and maintenance by using a smartphone application in those with overweight and obesity. Scientific Reports, behavioral therapy and weight loss.<\/li>\n    <li>Frankenfield D.C. et al. (2013). Validation of Mifflin-St Jeor equation in obese and non-obese populations. PubMed 23631843.<\/li>\n    <li>M&uuml;ller M.J., Bosy-Westphal A. (2015). Adaptive thermogenesis with weight loss in humans. Obesity, Minnesota revisit. PubMed 26399868.<\/li>\n    <li>Doucet E. et al. (2001). Evidence for the existence of adaptive thermogenesis during weight loss. British Journal of Nutrition.<\/li>\n    <li>Westerterp K.R. (2004). Diet induced thermogenesis. Nutrition and Metabolism.<\/li>\n  <\/ol>\n<\/section>\n\n<\/main>\n\n<footer>\n  <div class=\"wrap\">\n    <div class=\"row\">\n      <div>\n        <div class=\"kicker\">Lean &middot; lean-app.com<\/div>\n        <p>Article published on May 24, 2026. Updated regularly with user feedback and relevant new studies. Lean is available on iOS and Android.<\/p>\n      <\/div>\n      <div class=\"stores\">\n        <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n        <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <\/div>\n    <\/div>\n  <\/div>\n<\/footer>\n\n<script>\n(function(){\n  var bar = document.getElementById('progBar');\n  function up(){\n    var h = document.documentElement;\n    var sc = (h.scrollTop)\/Math.max(1,(h.scrollHeight - h.clientHeight));\n    bar.style.transform = 'scaleX(' + Math.max(0,Math.min(1,sc)) + ')';\n  }\n  document.addEventListener('scroll', up, {passive:true});\n  up();\n})();\n\n(function(){\n  if (!('IntersectionObserver' in window)) {\n    document.querySelectorAll('.rev').forEach(function(n){n.classList.add('on')});\n    return;\n  }\n  var obs = new IntersectionObserver(function(entries){\n    entries.forEach(function(e){\n      if (e.isIntersecting) { e.target.classList.add('on'); obs.unobserve(e.target); }\n    });\n  }, {threshold:0.12});\n  document.querySelectorAll('.rev').forEach(function(n){ obs.observe(n); });\n})();\n\n(function(){\n  var phoneImg = document.getElementById('phoneImg');\n  var phoneBack = document.getElementById('phoneBack');\n  var zones = document.getElementById('phoneZones');\n  var topTabs = document.querySelectorAll('.phone-tabs button');\n  var navTaps = document.querySelectorAll('.phone-navbar button');\n\n  var tabMap = {\n    bilan:    {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp',     drill:false},\n    kcal:     {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp',      drill:false},\n    depense:  {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp',   drill:true},\n    strategie:{src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp', drill:false}\n  };\n  var subMap = {\n    BMR:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp',\n    NEAT: 'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp',\n    EAT:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp',\n    TEF:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp'\n  };\n  var currentTab = 'depense';\n\n  function setActive(tab){\n    topTabs.forEach(function(b){ b.classList.toggle('on', b.dataset.tab===tab); });\n  }\n  function showTab(tab){\n    var t = tabMap[tab]; if(!t) return;\n    currentTab = tab;\n    phoneImg.style.opacity = 0;\n    setTimeout(function(){\n      phoneImg.className = 'phone-bg tab-' + tab;\n      phoneImg.style.opacity = 1;\n      zones.style.display = t.drill ? 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style=\"margin:48px auto;max-width:760px;padding:24px 28px;background:#ffffff;border-left:4px solid #FF2D6E;border-radius:0 12px 12px 0;box-shadow:0 6px 24px rgba(20,20,40,0.06);font-family:-apple-system,'SF Pro Text','Segoe UI',Roboto,Arial,sans-serif;color:#1a1a2e;\"><p style=\"margin:0 0 14px;font-size:13px;font-weight:700;letter-spacing:0.06em;text-transform:uppercase;color:#FF2D6E;\">Also read<\/p><ul style=\"list-style:none;padding:0;margin:0;display:grid;grid-template-columns:1fr;gap:10px;\"><li><a href=\"\/en\/comparatifs\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">All Lean comparisons face to the major calorie apps <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Hub: MyFitnessPal, Yazio, Cronometer, Lifesum, FatSecret, Noom.<\/span><\/a><\/li><li><a href=\"\/en\/lean-vs-myfitnesspal\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean vs MyFitnessPal: the TDEE formula that changes everything <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Why MyFitnessPal miscalculates your real calorie expenditure.<\/span><\/a><\/li><li><a href=\"\/en\/lean-vs-yazio\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean vs Yazio: scientific precision vs European ergonomics <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Honest comparison: BMR, NEAT, EAT, TEF, adaptation.<\/span><\/a><\/li><li><a href=\"\/en\/lean-vs-cronometer\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean vs Cronometer: micronutrient depth versus TDEE precision <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Cronometer sees your micronutrients. Lean sees your real expenditure.<\/span><\/a><\/li><li><a href=\"\/en\/lean-vs-lifesum\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean vs Lifesum: premium diet coaching versus TDEE precision <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Lifesum sells dietary wrapping. Lean rebuilds your TDEE continuously.<\/span><\/a><\/li><li><a href=\"\/en\/lean-vs-fatsecret\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean vs FatSecret: Premium precision versus the free community-driven database <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">FatSecret is free. Lean is precise. The hidden cost of free, explained.<\/span><\/a><\/li><li><a href=\"\/en\/alternative-myfitnesspal\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Alternative to MyFitnessPal: the 5 real options in 2026 <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Honest comparison: Lean, Yazio, Cronometer, Lifesum, FatSecret.<\/span><\/a><\/li><\/ul><\/aside>","protected":false},"excerpt":{"rendered":"<p>Lean TDEE Calculator Home &nbsp;\/&nbsp; Lean vs Noom Comparison &middot; Nutrition &amp; TDEE Lean vs Noom. Psychological coaching vs metabolic precision. Noom sells behavioral coaching to change your habits. Lean sees your real expenditure. Two promises that do not play on the same field. The Lean team &middot; Read 12&nbsp;min &middot; Updated [&hellip;]<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-lvm-blank","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1425","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Lean vs Noom: psychological coaching vs metabolic precision - Lean<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/lean-app.com\/en\/lean-vs-noom\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Lean vs Noom: psychological coaching vs metabolic precision - Lean\" \/>\n<meta property=\"og:description\" content=\"Lean TDEE Calculator Home &nbsp;\/&nbsp; Lean vs Noom Comparison &middot; Nutrition &amp; TDEE Lean vs Noom. Psychological coaching vs metabolic precision. Noom sells behavioral coaching to change your habits. Lean sees your real expenditure. Two promises that do not play on the same field. 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